Steve sits in with Katie Robbert, Co-Founder and CEO of Trust Insights, a marketing, analytics, and data agency.
Katie discusses the power of natural language, machine learning, and artificial intelligence to unlock insights from customer feedback. They give advice on how businesses can leverage tools to create a deeper understanding of their customers' needs, beyond just conversion.
The conversation also dives into the intersection of marketing and technology, offering tips for those working with developers. Other topics discussed include Google Trends, the potential for an Apple-Google merger, the psychology of marketing, being patient in your technology journey, and advice they would give their younger selves.
Tune in to learn more!
Key learnings from this episode:
Connect with Katie Robbert and Steve Goldhaber on LinkedIn.
With 25+ years of marketing experience, Steve Goldhaber is a former head of global digital marketing for two Fortune 500 companies and the current CEO of 26 Characters, a content marketing agency in Chicago.
Connect with Steve on LinkedIn.
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Steve Goldhaber: Hey everybody, it's Steve. Welcome to Studio 26 and the interesting B2B Marketers podcast. I'm really excited today. Katie, welcome officially to the show. Thank you for being here.
Katie Robbert: Thank you for having me, Steve. You know, it's funny, I don't consider myself interesting, but I guess we're about to find out.
Steve Goldhaber: Well, you know, I guess the most boring B2B marketers I could have, I could have put it that way. That may have caused more intrigue because it would be like a contest. Who can be that boring? No, we all are. I'm a big believer in the fact that we are all very interesting. We're just not interesting to ourselves because we know ourselves, but other people always find this interesting. Alright, and we're gonna find out more about that in a second what makes you interesting. But give us a 60-second intro before we jump into the case studies.
Katie Robbert: Yeah, absolutely. So I'm Katie Robbert. I am Co-Founder and CEO of Trust Insights. We are a marketing, analytics and data agency. My role is to basically herd the cats, keep our data science team in line client relationships. And when I'm not doing that, I'm hanging out with my dog. I'm outside and untethered and not on my computer. So I sort of have this duality of my life.
Steve Goldhaber: Yep. All right. We're jumping into case study one. Now, this has to do with the term that I, I learned many years ago and I didn't quite understand governance. And the way that I learned it was I worked with an extremely large company, right? And governance was essentially the code word for its big, it's complicated. We need rules to the road. We need to manage all this stuff. So you're gonna talk about governance as it relates to. Google Analytics. Take it away.
Katie Robbert: Yeah. So, and just sort of an aside, my background is in clinical trials and pharmaceutical work. So data governance was essential. And so when I switched over to commercial b b I started working with this client who. They were trying to get their web tracking set up correctly. They have, they're an enterprise-sized client and they were struggling to really make sense of their data. And so the first thing we said was, why don't we take a look at the infrastructure of your marketing tech stack, because that's usually where the problems start. And so specifically they were using Google Analytics to track their website activity. What we found when we took a look at their system was that it wasn't configured correctly at all. So they had. Almost all of the traffic coming into their website was unattributed, meaning you couldn't tell if it came from Twitter or LinkedIn or an email marketing newsletter or an organic search. And they were spending a lot of money on their digital marketing activities. And so we were able to restructure and clean up the configuration of their Google Analytics instance.
We talked through with, you know, what kind of goals, what are the conversions that you wanna see captured? And once we did that, They started to see better data come in. But the second half of that is that we had to introduce data governance, which meant that we needed to help them understand the correct process and management of how they were tagging things outside of their website so that when it came back into the system, it was coming through with good data integrity. So once we did those two things, we, once we fixed their system and introduced data governance, they were able to Clean up about 70% of their unattributed. Oh wow. Traffic. And finally do some attribution reporting. Make some decisions. It was a big deal for them.
Steve Goldhaber: Interesting. Now, the beauty of Google Analytics is, oh, it's so easy. You just take this little piece of code. You find someone who knows what a source is, you know, find the source code, and paste it in the header or the footer, right? Like I imagine that you see clients make that mistake. Over and over. Is that right?
Katie Robbert: I do. And you know, I think Universal Analytics, which is the previous version of Google Analytics, was a little bit easier to navigate. The newer version, Google Analytics four, which officially becomes the version on July 1st of this year, is exceedingly more complicated for no good reason. They now have, you now have to use Google Analytics and Tag Manager and BigQuery and Data Studio and you know, all of their products. And this is by design from Google. And so for a company who doesn't have the time or resources or core company to set these systems up correctly but are reliant on the data to make decisions, is pretty much gonna be up Creek. And that's where yeah, you know, I come in.
Steve Goldhaber: Yeah. So why, why has Google done that? I mean, besides, you know, secure future tech jobs for the next 50 years, right? Like, why, why w would a company that is so good at making things simple through technology make it so hard? Any theories on that?
Katie Robbert: The unofficial reason is that they turned Google Analytics four into, basically they took Firebase, which was their mobile. Web tracking app that was a companion to Google Analytics, three Universal Analytics, and they basically re-skin that as Google Analytics four. Their public reasoning was so that we marketers could have a better time across across different devices, sort of tracking users across the devices. Okay. And it also introduced a lot more data privacy hoops, which in a way is a good thing. But for cust, for marketers who are talking about that single view of the customer. Yeah, they're definitely not gonna get it from Google Analytics.
Steve Goldhaber: Yep. All right. Now I'm gonna take this case study and I'm gonna sidestep a little bit cuzwe're into an interesting data privacy thing. Tell us about like Google Analytics ecosystem as it relates to what Apple is doing and how they're trying to create their own, kind of like, Hey, we're not the bad guys, we're the good guys. Like, help us understand how to migrate those two different ecosystems.
Katie Robbert: So with Apple and with Google. So there was a, there was a lot of talk late last year and earlier this year about a cookie list future. And so basically what that means is that, Companies like Google and Apple are making it their mission to protect the end user, to protect the consumer, to protect data, protect privacy, especially when you have regulations like GDPR out of the eu and you have C C P A out of California, which really make it more, more important that we all abide by certain data privacy regulations, what that means for marketers is that we can no longer be lazy. We can't rely on, you know, cooked websites to track people, to track their activity. We actually have to get off our butts and talk to people and say, what did you want? What do you, what do you like about us? What don't? And so it's, in a way, it's a resurgence of a voice of customer. If companies are willing to put in the work, otherwise they're just gonna lose a lot of data.
Steve Goldhaber: Yeah. Never underestimate the power of a marketer to be lazy. So don't, don't assume that we can shape that behavior. There are lazy marketers all over there. It's true. So back to the case study. Like what, what's the, you mentioned the outcome was better attribution. I'm assuming that there's just now they're in a place to make better decisions. What, what are the other, some of, some of the benefits that came from that governance process?
Katie Robbert: So what the client was able to start to understand was, were they spending money in the right places? And so this particular client has a tendency to just sort of throw money at different marketing channels depending on. Which one they think is gonna bring them in the most conversions. And so what we've been working on with them is actually using their attribution data to make smarter decisions to say Your email marketing is doing well, but you don't need to throw a hundred percent of your budget at it right now. Perhaps you should also be looking at your organic social media, which drives a lot of awareness. It's sort of more of the top of the funnel versus the bottom of the funnel, which is a whole different struggle. For them to wrap their heads around, cuz most companies, especially enterprise-size companies, are focused on the conversion, not the awareness. And so there's also that education of if you bring them in at the top of the funnel, they will eventually get to the bottom.
Steve Goldhaber: Yep. All right. Nice. All right, let's jump into case study number two. This is a sexy topic, natural language processing. I have become mildly obsessed with this category, so I'm, I'm eager to hear you share your thoughts on this case.
Katie Robbert: So, As a disclaimer, we did this project prior to GPT becoming a household phrase, and so this was a few years ago, a client approached us and said that they were struggling to understand what their customers really wanted. The reason is because all of the customer feedback data was tied up in the call center, and so the call center, as you can imagine, is just like thousands upon millions of phone calls that may or may not be transcribed. And so they didn't have a good way to get into that day to figure out what product should we be thinking about competitively next? And so this client creates beverage thickeners for alternative dairy beverage. So it's a very, you know, specific market. And for them to understand what clients want, they really need to get into that data. So what we were able to do was extract. The call center data have it transcribed, and so basically what we had was this just a big pile of unstructured content using natural language processing, which is a lot of what GPT does. What we basically did was created a script that found the common terms. So basically topic modeling to say what are the common themes and phrases taking out, you know, all of the ifs and buts, like words that don't really mean anything. Yeah. And what we were able to find out is that customers were asking desperately, For an oat in the almond alternative, they were looking for something like hemp milk. So you can imagine, sort of timeframe-wise, this was a few years back, hemp milk wasn't really a known thing yet. So this company had the opportunity to say, oh, we should probably develop some sort of a thickener for hemp milk using that as the base. We wouldn't have otherwise known that if we hadn't done this natural language processing. And so it became recurring. Quarterly project for them to figure out what are we missing.
Steve Goldhaber: That's fascinating. I've always been so into like, you know, I used to manage call center marketing teams and there's just such a rich area to learn and I would always listen in on customer phone calls cuz it was just fun to see them react to marketing campaigns or struggle to find like how packages were structured. And I'm amazed that more companies don't do this, whether it's just talking to their call center people or, or adding just little like quick surveys when you're done with a call. Like, Hey, just here's the one question. Can you answer it for us? That's kind of fascinating. How long does that take to do? So once you've got that data, you said you wrote a script. How fast is that?
Katie Robbert: Well, it depends on. How much data we're working with? And so at the time when we did this a few years back my data science team my chief data scientist was processing this on his laptop. And so as you can imagine, it took longer than if he had built yeah, a data warehouse in the cloud. We were a very small business just starting. And so for us, we just couldn't, we couldn't afford those resources at the time, but we knew we could do the work and so he basically would have his laptop just sort of sitting like a brick, just running data, I think, to process everything on and off. It took about 48 hours to use up all of his CPU. But now, fast forward, if we were to do this again, we now can do this virtually in a data warehouse. Yeah.
Steve Goldhaber: I gotta say, like I subscribed to Otter years ago, and I loved the ability to just quickly go, Hey, I remember I had a conference call with someone, or a webinar, whatever it was. And like the example I use is like, someone made a reference to a penguin. And that penguin was like, I know that there was like something I needed to find right by that penguin resource. And I love the ability to go in, have AI generate all that text and just say, Hey, all I have to do is type penguin. And two seconds later I can click on that audio and go, yes, that's what I was looking for. So, It is amazing the last couple of years how precise you can get and how strange that works with my brain. Like I, I have the ability to remember ridiculous reference points. Mm-hmm. Sometimes and I can grab that in AI-generated text and, and get to something very quickly. And of course that is just proliferated everything now has the ability to basically like, oh, that's just a plugin and now you have AI or audio conversion in it. Is that something that, that more your clients are kind of like, Hey, give me that I hear more of this.
Katie Robbert: Yeah, absolutely. And so we've been spending the majority of our time talking and educating pretty much anyone who will listen on the power of large learning models and like G P T and the other ones that are out there. What's interesting, what strikes me, and I didn't make the connection until you and I were talking, is that this. The case study is sort almost like phase two of the previous case study where you were asking about what does data privacy mean for marketers who are looking to collect that information? And this would be the way that they would start to do that. So you would hope that they would start, you know, using these large language models to gather that rich information. You would think so. But to your point, we have a tendency to be lazy.
Steve Goldhaber: This is just gonna turn into the Lazy Marketers Podcast. We're just gonna, we're gonna call out all those lazy marketers. Alright, let's jump into case data number three. This one has to do with the SEO field, specifically around predictive analytics.
Katie Robbert: So we had a client come to us and say they wanted to show up in Google, as you know, the number one PR firm in their particular region, which is not an insignificant ask. So the first thing I always tell people is don't Google yourself. That's just not how organic search works. But what they were trying to do was outrank their competitors and it's not enough for them to just put on their website. We're the best in the business. So what we did was we did a competitive s e o audit for all of the topics, the keywords that their competitors were showing up for in Google search. And we said, where are there opportunities? Where are there high-ranking keywords with not a lot of volume? And then also where are the low-ranking keywords with a lot of fog? So we could sort of see where there was white space in between the two sides of the keyword research. But then what we did was use a Rema model. We u we generated a predictive forecast using SEO research and also Google Trends data. So if you're unfamiliar, Google Trends should be a marketer's best friend. You can go to Google Trends for free. You can type in a keyword and it's gonna give you a sense of when people are searching for a particular keyword or topic so you can see the seasonality of it. And so using. Google trends, we were able to map out 3, 6, and 12 months for them, the time in which people would be looking for those particular keywords that they wanted to rank for that was going to get them higher up in the rankings in Google search for the best PR agency in that particular region. And so I'm Yeah, go ahead. I was gonna say we were able to help them increase that traffic by 40% by using that method.
Steve Goldhaber: I was gonna say, I'm always amazed by Google trends and how long it's been around and how people still don't know it's a resource and you get some ridiculous use cases. For example, like there's a whole flu tracker every year. Where by region you can see based upon who's typing like, Hey, I have these symptoms, or What are flu symptoms? It's, it's amazing to have this living, breathing organism that you can just watch and go, wow. We can predict all these things. Why isn't that, I don't mean to be so hard on Google on this call, but like, why is it that they're not more that data isn't more accessible, more people, and, and maybe that's not even the right way to say it, because it is, it's very accessible, right? But people don't know about it. Why do you think Google always struggles with that?
Katie Robbert: Because Google is a company run by developers. And I don't mean to pick on developers, but developers I can. I can a little bit because I manage development teams for over a decade and I know their personalities and they are. In their hearts, their customer first, but in their heads, their technology first. And so they don't think about the ease of use necessarily. They don't think about the use cases. They think, does this technology work? Is it a sound piece of software? Can you export the data? Great. That's your problem. Now you've got the data. Go do something with it. Yeah, and so it's the same thing with Google Analytics. It was created by developers without really thinking about the end user.
Steve Goldhaber: Yeah, that makes sense. We should, we should orchestrate Apple and Google merger to take the front-end design, you know, customer-centric thinking and apply it to the backend. Of course, that would never work out because it would take so while take, take such a long time for those companies to merge and we would then destroy both companies and not have anything to show for it.
Katie Robbert: But now you've put it out in the ether. So maybe it'll happen.
Steve Goldhaber: Maybe. Someone's recording this podcast right now with some N L P scripts. And Tim Cook is listening cuz he tunes in to us for all his ideas.
Katie Robbert: Maybe. I think that's a plausible use case.
Steve Goldhaber: I like that. It is totally plausible. Wouldn't that be great if like, You know, just randomly you get Tim Cook to be on the podcast just outta nowhere? Like, yeah, I'll do it. Sure.
Katie Robbert: That would be a big Get that. Yeah. Now see, that's an interesting B2B market.
Steve Goldhaber: There you go. He'll be like, well technically I don't market it. I just please customers. That's what I do. That's how he would phrase it. All right. Let's jump into the Q and A part. Tell us how you got started in marketing accidentally.
Katie Robbert: I actually have a film degree. And so with my film degree, I went on to work in clinical trials, so totally, you know, a natural leap. What ended up happening was I got my film degree and I live in New England, and the film industry hadn't come to New England yet. So as a 22-year-old kid, I could not afford to move to New York or California. So I needed to find something else to do with my time. So I ended up working as a product assistant. At a company that was half academic, half commercial. And that's where I started to learn a lot about things like data governance, about development, about marketing and sales. And so over the course of about the decade that I worked there, I became the product manager. And that's where I started to learn about marketing. And so when I went to grad school I got a. Master's in marketing and technological innovations, cuz I really liked the blend of marketing and tech. And so when I moved on from that job, I actually joined as the director of a marketing technology team, which is where I then met the co-founder of my now company. Trust Insights.
Steve Goldhaber: Yeah.Okay. I gotta say so many people I've had on the show answer that question the same way they do. I, I accidentally got started in marking, and then all of a sudden like, It was actually really fun. So it's such a strange pattern. I wonder if that is true for most marketers. I got started in communication, so I like to have a degree in communication. So in my mind it was always, I love, I love the process of speaking. And trying to sell something, but I feel very lonely. I feel like I don't have as interesting of backgrounds as our guests, but of course, that's why they're the guests cuz they're interesting B2B marketers. What is it to this day that you just love about marketing?
Katie Robbert: The psychology of it. So what I really enjoy is trying to meet people where they are and understand what is it they actually need. Versus a company just telling someone what they need. And so we were having this conversation this morning when we were talking about a lot of natural language processing and one of the things that's really interesting about it is that natural language processing like chat G P T is really going to allow marketers to get a better sense of what the customer wants. Without necessarily talking to the customer, because it's all of this sourced information versus you saying, this is what you're gonna have, this is what I'm marketing to you. So for me, it's always been getting into the head of the end user.
Steve Goldhaber: Yep. All right. I'm gonna pick up something that you spoke on before, as you alluded to the people at Google and the, and the developer mindset. You know, you run a business, you've gotta work with the developers all the time. What do you know, what advice do you give to the marketers listening to the podcast to say, you know what? Here's the, and, and I also, I'll say this big caveat here, like, I don't think there's a one size fits all management approach. So I'm not looking for like the one thing that you recommend, but like, as you've worked with all these developers over the years, what does work well? What are some recommendations on how to have a good relationship with each other?
Katie Robbert: I would say the number one piece of advice that I give to managers managing a technical resource is don't assume that they are smarter than you. It's just a different skill set. It's you having respect for yourself and your intelligence and your authority and what you bring to the table goes a long way for them also seeing you that way. So, you know, Steve, if you said to me something about, you know, Google's algorithms and natural language processing. The worst thing I could say to you is, okay, explain it to me like I'm stupid, because then what I'm doing is I'm signaling to you that I think I'm stupid. Therefore you should also think I'm stupid. And that just sets the relationship off on the wrong foot. And so a better question would be help me understand what that means for our customers. Help me understand why this is the solution that you've chosen and not something else. And it gives the developer or technical resource or data scientist an opportunity to step back and say, did I choose the right thing? Or how would I explain this to the customer instead?
Steve Goldhaber: Yeah, that's great advice. I have, I have said my own version of that. I don't say, explain to me like I'm stupid, but I go to the default. Explain it to me like I'm a first grader. Same thing. Yeah. And it's the same thing. Like it. I really like the way that you reframed it. Because you're, you're communicating. I don't have the context for what this means. And you also need to put on your, we're working for a company, trying to help customers hat. So I really like that. Maybe let's do a little deep dive into the N L P world. And of course, by the time the podcast gets Published, it'll be all outdated because that's how fast that world is moving right now, but mm-hmm. What do you, what do you see happening besides the obvious ones, like generative content or you know, open AI has announced a plugin economy that essentially accelerates the way that data gets consumed and learns. Like, what do you, what do you think the longer-term implications of all this are?
Katie Robbert: I'm actually. I think I'm firmly in the, I'm excited about at camp. I'm not worried that AI is gonna take my job. I'm excited for the things that it's going to automate about my job. So one of the things that large language models like G B T is gonna be able to do is put together a marketing strategy if given the right information or it's already able to interpret a presentation or a chart. And say, these are the insights that I found. And so having that ability to scale, especially as a small business to me, is invaluable because then what I can do is I can focus on the actions, the insights, the relationships, all of those human tasks that can't be replicated. So I'm happy, let the machine go ahead and put together a plan for me. I can then spend my time refining it and customizing it.
Steve Goldhaber: Yeah. All right. I'm gonna jump into things that drive you crazy Now. We, we both are service providers. Yeah. This is season two on things that drive you crazy. So you work with a lot of clients. Mm-hmm. And what I've learned over the years is like every client's at a different spot, you need to be really patient and understand where they are and where you can get them. What are some for all the, all the good and maybe bad clients out there? What do you suggest as they jump into the world that we've been talking about today? Give us like a little bit of advice on like, do these things, don't do these things, you know, what would you say?
Katie Robbert: This is the hardest part because there needs to be a certain level of self-awareness of where you, the client, are in your technology journey, in your data journey, in your artificial intelligence journey. And so if for example, you don't have good data integrity and data governance for a system like Google Analytics, you're not ready for artificial intelligence because those are the foundational building blocks. Before you can even get into the more advanced technology. And I think that that's gonna be the biggest challenge, is having patience. I wanna go play with the shiny object. I wanna play with a toy. I wanna have chatGPT, write 500 blog posts for me and fire all of my writers. It's absolutely the wrong way to approach it, and I think that that's gonna be the biggest struggle for people, for clients, for companies trying to get on board. Those foundational building blocks, it's sort of the same of, you know, I can't just wake up and run a marathon if I haven't spent months and months and months of training and conditioning. I can try and I'm gonna feel miserable and I'm gonna hate myself for it. But if I put in the work from day one, maybe do a couch to 5k, maybe decide that I should probably get running shoes and not running flip flops, then I would have an easier time. It's gonna take longer, but it's going to set me up for success in the long run.
Steve Goldhaber: Yep. That makes sense. All right, I'll, I'll switch to the more optimistic side of the podcast. We're taking this show into a very, like, people are bad data is horrible. They're gonna get you.
Katie Robbert: Which is funny cuz I'm the people person on the tv.
Steve Goldhaber: Yeah. All right. We're gonna be positive. Now. What, what about your best client ever? What are some things that they did where you're like, oh my God, yes. Do more of this.
Katie Robbert: The characteristics of some of our really great clients are people who are just open to hearing the good and the bad. And so when a client says, give it to me straight. Tell me how broken it is, what do I need to do to fix it? I'm invested. That's a really great client cuz that tells me that they are really wanting to be set up for success and that they will be successful. It's sort of that flip side of the clients who just wanna skip ahead to like the fun, shiny objects, but there's nothing holding it up. Yeah. And so it's, it's the clients that are just very open and honest and responsive and not trying to hide the things that have gone wrong. Yeah. I mean, we don't get everything right in our own company. We just have to be aware that sometimes mistakes happen, we acknowledge them and then we move on.
Steve Goldhaber: Yeah, I think that's, that's pretty interesting and consistent with what I see in some of my best clients. I, the ones I've enjoyed the most relationships with, just have no No false expectations that they know at all, and they're great. Mm-hmm. At everything. They, they start out the conversation with like, here's what I got, here's what I'm, you know, I've had clients be like, here's what I'm really good at. I'm horrible at this and I need your help with this, and I trust you to help me with that. And, you know, sometimes that's, that's hard for clients to do. They view it as such a, like, no, I'm in a position of power and authority. Mm-hmm. And if I concede any knowledge that I don't have that helps or that hurts me with, You know, negotiating a contract or trying to get something that they need. Usually, the people who are the most humans are the ones that you then understand and care for and help out as opposed to those who just kind of try to cram things through. So, yeah. Interesting. All right. Last question. This is gonna be more reflective on your career. So you've been, you've been doing it for a while. If you could go back in time and tell yourself like your first week of when you started working, Hey, do this, or Don't worry about that. What are some things looking back that you would've done differently?
Katie Robbert: It's interesting and ironic because the advice that I now give to my clients is the same advice that I needed to give to my younger self, which is to don't skip over the foundational pieces, the building blocks. Don't get too ahead of yourself. So I've, I'm someone who's always been looking for the next thing I was looking for, the promotion for the next step. I, I would see that someone else was doing something and say, I wanna do that. And my manager at the time, rightly so, would tell me to slow down, be patient. Focus on what's right in front of me, master that first, and then I will be ready to go on to the next thing. And I was very impatient. I wanted to, I was ready to be the c e O at 22, but I knew nothing. But I was like, but he's over there doing it. I can do it too. Yeah. And I knew nothing. And so it really was, I'd say the advice would be, be more patient and do the work.
Steve Goldhaber: Yeah. I can relate to that because I remember, I remember in my early twenties, and I would read a job description for like, you know, the next level up and I would be like, I can do all these things. Like, it's just, it's so clear. Mm-hmm. But Steve, you've never managed a team before. But okay, I can do that. And it's like, well, it's not that easy. And I, and I think we always, with age in our careers look back and go, oh, that totally makes sense now. Yeah. Like, Maybe I could have managed a team, but that team had to have all been high performers who didn't have any challenges or need growth in certain areas. Yeah. But, but all of a sudden you find yourself in a situation with, Hey, there's, you've inherited a team and you need to manage them. And there's like, that's not a you don't go to the team management webinar and, and 60 minutes later figure out how to manage a team like it. I still, you know, I still try to figure out how I can be a better manager of teams when I've been doing that for over, over 20 years. It's like, I don't think you can ever, there is no finish line using, using your kind of marathon analogy from before, there is no finish line. Perhaps when we are dead, that is the finish line. Like you are, you are, you will now no longer learn about human nature and how to, how to manage teams, but.
Katie Robbert: I don't know. I am honest with people who are gonna be haunted by me. So I think it's just gonna keep going and going.
Steve Goldhaber: I've certainly taken this podcast, into dark and evil places. I don't know what's going on.
Katie Robbert: Maybe I think it's me. I think I'm forcing you into these darkened, interesting people. You know, it's in terms of the management, you know, again, looking back. There was a time when I inherited a team that I didn't really know much about any of the players, and at no point in any of my management trainings or experience was I prepared to navigate a three hour, you know, cry fest by two team members over whether or not we were a firm that used AP style. Oh my God. Yeah. And so those are the things that you just, you know, nothing prepares you for that. Yeah. And unless you have enough experience, I mean, I still to this day am like, I don't even know if I handled that cor correctly. Like it didn't matter what the answer was. Yeah. It was more about the heightened emotions of the two team members.
Steve Goldhaber: Yeah. I've had similar moments looking back in my career that I started to change. So like when I was, when I was new or like I was brought in as the new leader of whatever team, I made it a point. To try not to ever talk about work in my first meeting, and I tried to do it over lunch or coffee and just get to know them as a person and try to just disclose. I am not here to talk about work un, unless you need to. Right? If you, if you absolutely want to talk work, we can talk work, but I tried to always set that, that first meeting and connection up as a human one, because in the past I was like, Steve, the happy marketer who was like, let's just jump into it. What's going on? What are you doing? How can I help? You know? And you know I, that's my own advice if, if I was asked the same question, it's always like, be a human first and a marketer second, because mm-hmm. Without the humanity of it all, the, the marketing doesn't mean anything. Or, or it's harder to do if, if you're not connecting in meaningful ways with people. All right, well, you have, you have proven yourself. Incorrect in that you, you disclosed yourself as not interesting. You were very interesting. I had a really interesting conversation and I don't mean that in the weird, like, you know, some people use the, oh, that's interesting. Like, she's interesting. It's, it's good. Interesting. Not bad. Interesting.
Katie Robbert: I mean, I've been called both versions and I'm not offended by either.
Steve Goldhaber: Yeah, that should be, that, that needs to be a LinkedIn profile description is like, I'm the good, interesting person, not the bad, interesting person. All right. Well, Katie, thanks for joining us on the show today. Remember everyone who's listening or watching, like, and subscribe. And until next time, have a great job doing all your great B2B marketing. Everyone. Take care. Bye-bye.